Evidence map›Paper›PMID 38961461›Full record

ArticleBMC health services research2024

Efficiency evaluation and promoter identification of primary health care system in China: an enhanced DEA-Tobit approach.

Zhi Zeng, Xiru Yu, Wenjuan Tao, Wei Feng, Wei Zhang

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Article in BMC health services research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Zhi Zeng *Institute of Hospital Management, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, China.
Xiru Yu *Institute for Hospital Management, Tsinghua University, Shenzhen, Guangdong, 518055, China.
Wenjuan TaoInstitute of Hospital Management, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, China.
Wei FengWest China School of Public Health, West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, 610041, China.
Wei ZhangWest China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, China. Weizhanghx@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith Primary Health Care (PHC) being a cornerstone of accessible, affordable, and effective healthcare worldwide, its efficiency, especially in developing countries like China, is crucial for achieving Universal Health Coverage (UHC). This study evaluates the efficiency of PHC systems in a southwest China municipality post-healthcare reform, identifying factors influencing efficiency and proposing strategies for improvement.

methodsUtilising a 10-year provincial panel dataset, this study employs an enhanced Data Envelopment Analysis (DEA) model integrating Slack-Based Measure (SBM) and Directional Distance Function (DDF) with the Global Malmquist-Luenberger (GML) index for efficiency evaluation. Tobit regression analysis identifies efficiency determinants within the context of China's healthcare reforms, focusing on horizontal integration, fiscal spending, urbanisation rates, and workforce optimisation.

resultsThe study reveals a slight decline in PHC system efficiency across the municipality from 2009 to 2018. However, the highest-performing county achieved a 2.36% increase in Total Factor Productivity (TFP), demonstrating the potential of horizontal integration reforms and strategic fiscal investments in enhancing PHC efficiency. However, an increase in nurse density per 1,000 population negatively correlated with efficiency, indicating the need for a balanced approach to workforce expansion.

conclusionsHorizontal integration reforms, along with targeted fiscal inputs and urbanisation, are key to improving PHC efficiency in underdeveloped regions. The study underscores the importance of optimising workforce allocation and skillsets over mere expansion, providing valuable insights for policymakers aiming to strengthen PHC systems toward achieving UHC in China and similar contexts.

Indexed as

Efficiency, OrganizationalHealth Care ReformPrimary Health CareChinaHumansChinaData envelopment analysisEfficiency evaluationHorizontal integrationPrimary health careTobit regression

Identifiers

PMID38961461
PMCPMC11223419

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.